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Massive multiple access based on superposition raptor codes for M2M communications

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posted on 2025-05-11, 13:03 authored by Mahyar ShirvanimoghaddamMahyar Shirvanimoghaddam, Mischa Dohler, Sarah JohnsonSarah Johnson
Machine-to-machine (M2M) wireless systems aim to provide ubiquitous connectivity between machine type communication (MTC) devices without any human intervention. Given the exponential growth of MTC traffic, it is of utmost importance to ensure that future wireless standards are capable of handling this traffic. In this paper, we focus on the design of a very efficient massive access strategy for highly dense cellular networks with M2M communications. Several MTC devices are allowed to simultaneously transmit at the same resource block by incorporating Raptor codes and superposition modulation. This significantly reduces the access delay and improves the achievable system throughput. A simple yet efficient random access strategy is proposed to only detect the selected preambles and the number of devices which have chosen them. No device identification is needed in the random access phase which significantly reduces the signalling overhead. The proposed scheme is analyzed and the maximum number of MTC devices that can be supported in a resource block is characterized as a function of the message length, number of available resources, and the number of preambles. Simulation results show that the proposed scheme can effectively support a massive number of MTC devices for a limited number of available resources, when the message size is small.

History

Journal title

IEEE Transactions on Wireless Communications

Volume

16

Issue

1

Pagination

307-319

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Language

  • en, English

College/Research Centre

Faculty of Engineering and Built Environment

School

School of Electrical Engineering and Computer Science

Rights statement

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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